Principal Software Architect

Microsoft • Redmond, WA

3d

About The Position

Do you want to be at the forefront of innovating the latest hardware designs to propel Microsoft’s cloud growth? Are you seeking a unique career opportunity that combines technical capabilities, cross-team collaboration, with business insight and strategy?
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to achieve our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
The SPARC organization manages Azure’s hardware roadmap from architecture concept through production for all of Microsoft’s current and future on-line services. This role is for a Software Architect with a strong background in hardware-software co-design, performance modeling, system architecture, and large-scale AI workloads. The ideal candidate will have experience building simulation frameworks, architectural models, and software prototypes to evaluate next-generation AI accelerators and cloud-scale AI systems.

Requirements

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

• Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• MS/PhD in Machine learning, Computer Architecture/Systems, Electrical Engineering, High-Performance Computing or related areas.
• 10-15+ years of experience developing/architecting high end AI Simulators / Accelerators.
• Experience with GPU and AI accelerator architectures, including compute pipelines, memory hierarchies, interconnects, and parallel execution models.
• Strong programming and scripting skills in Python and C/C++ for performance analysis, tooling, benchmarking, and automation.
• Experience with architectural modeling or simulation frameworks, and correlating modeled behavior with measured hardware performance.
• Strong understanding of AI and HPC workloads and how they map onto large-scale accelerator- and GPU-based systems.
• Ability to communicate complex technical concepts clearly through design documentation, performance reports, functional specifications, and technical presentations.
• Strong colloboration and cross-team communication skills.
• Experience with frameworks such as Pytorch/Tensorflow/TensorRT.
• Familiarity with modern AI serving stacks such as vLLM and SGLang frameworks.
• Understanding of transformer architectures and optimization techniques, including quantization, sparsity, sharding, KV-cache management, and Flash Attention.
• Knowledge of commonly used AI and HPC workloads and how they are mapped onto large scale systems.
• Knowledge in developing kernels or low-level optimizations for AI accelerators / GPUs.

Responsibilities

• Develop simulation, modeling, and prototyping frameworks to enable early architectural exploration and performance analysis of next-generation AI accelerator platforms.
• Analyze and model large-scale AI training and inference workloads, evaluating how they map onto GPU and accelerator architectures.
• Perform performance analysis and benchmarking across GPUs and in-house AI accelerators to identify bottlenecks, scalability limits, and architectural trade-offs.
• Correlate simulation models with real system measurements and workload traces to validate architectural assumptions and improve model fidelity.
• Build and evolve software tools and infrastructure for architectural modeling, analysis, and performance visualization.
• Work across hardware, software, compiler, and systems teams to understand workload behavior and guide architectural optimization.
• Provide data-driven insights and recommendations that influence future AI accelerator and large-scale system architecture decisions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level